Electronic test equipment is used to check devices throughout their assembly and operation, tracing any faults and reducing scrap/increasing productivity. Here, Yonatan Hyatt, CTO of Inspekto, discusses how autonomous machine vision could improve these component tests


lectronics companies should inspect their surface-mount devices (SMDs) to ensure that the components are present, of the correct type and assembled in the right location, at the correct orientation.

Businesses can opt for manual visual inspection, or a machine vision solution, to check for abnormalities that could impact the functionality of the PCB. However, as parts become increasingly complex, manual inspection is less feasible, making machine vision essential going forward.

SOLVING THE QA CHALLENGE Unlike a traditional solution, autonomous machine vision systems give quality assurance (QA) and plant managers complete control. They require little cost, effort and time to install and run. Importantly, rather than handing the reins of a machine vision project over to an external systems integrator, electronics businesses can do it in- house, without the need for training. Defining how it operates, the system’s algorithm optimises the camera and illumination settings for the object and environment, detecting and locating the object without any input from the operator. The system’s artificial intelligence (AI) engines imitate the work of the expert machine-vision integrator. Then, the system only requires a limited number of good sample references to, ultimately, recognise the properties of a gold standard product: whether it be an issue with soldering, a missing component or simply that their arrangement is too intimate, the defect will be flagged and acted on.

QA IS EVERYWHERE If the manufacturer then decides that the system would be best consigned at another point on the production line, it can be moved as and when required, set up in just a few minutes. Alternatively, one can purchase multiple systems to install at every required point on the line. This is because the system can be purchased at one tenth of the cost of a traditional solution, and will adapt to each new product and environment in mere minutes.

Autonomous machine vision therefore enables total visual quality assurance at every step of the production line. The manufacturer can identify a defective product at the exact stage that the defect originated from. This improves yield and prevents scrap; no further time or energy is wasted on a defective part, avoiding its amalgamation with an efficient part later, which could result in a faulty product.

In electronics assembly, the process often results in variations in shape tolerance, particularly when working with printed electronic parts from different providers. There is also the potential for electronic parts to bend or break during assembly, and it is possible that the wrong components have been added, parts are missing, are of the wrong type, or are in the wrong location. Traditionally, these issues would go unnoticed until the end of line test, when the electronic device would fail. However, by using total QA, the manufacturer can identify a defect as soon as it is introduced. Total QA also enables the manufacturer

Inspekto’s S70 - the company’s answer to its vision of autonomous machine testing

to optimise their line. By performing root cause analysis, using data that examines the full picture, the QA manager can trace a defect back to its source. They can then take action to replace or perform maintenance on the equipment at fault, and prevent defects from being introduced in the future. In this way, the manufacturer can optimise and streamline their plant, protecting their customers from defective products and protecting their facility from scrap and flawed manufacturing processes. Autonomous machine vision has kickstarted a revolution away from complex, cumbersome and expensive solutions installed by a systems integrator. Instead, manufacturers can accurately, affordably and immediately inspect products at any point on the production line.




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